By Rob Hyde and Michael Leidig
ARTIFICIAL intelligence (AI) companies are suddenly paying staggering sums for journalism after years of scraping news content for free.
In an apparent gold rush, the last couple of year have seen the industry buzzing with blockbuster agreements ranging from Google’s reported $60 million-a-year deal with Reddit to OpenAI’s five-year News Corp agreement said to be worth more than $250 million. And Meta, Amazon and other giants have also signed partnerships with publishers including the New York Times, Financial Times, Le Monde, Associated Press and Axel Springer.
At first glance, the message seems simple: AI companies need journalism and are finally willing to cough up for it. But despite these eye-watering deals between the giants of AI and news publishing, can ordinary journalists and smaller publishers realistically make a fair buck too?
Some legal experts suggest there is actually considerable grounds for hope when it comes to journalists and small publishers standing up to AI giants, by focusing on EU law.
Eleonora Rosati, Professor of Intellectual Property Law at Stockholm University, specialises in copyright and the legal implications of AI for publishers and creators. Speaking to The European, she said: There is definitely a market for this type of content, given its quality and timeliness, which are both key to high-quality training results.
And she pointed to growing legal and political pressure across Europe, which should work in favour of those producing content.
“Regarding individual journalists, they would be entitled to part of the remuneration generated by press publishers when negotiating deals pursuant to their press publishers’ right under Art 15 of EU Directive 2019/790.”
But others are far more sceptical. German national Ulrike Langer, who describes herself as an “AI in journalism analyst”, has spent years covering media innovation, AI and publishing strategy for German-speaking media executives and publishers. Based in Washington State, she regularly writes and speaks about newsroom AI, licensing deals and the future of digital publishing.
Speaking to The European, Langer said the current licensing market already has a clear hierarchy.
“The market has two tiers,” she said. “The top tier is real: Reuters, AP, AFP, and the Meta-News Corp deal involve serious money for structured news feeds.”
But below that level, she warned, the economics rapidly collapse.
“The second tier — everything below the global agencies and the largest publishers — is mostly still a conference talking point. Industry-wide deals may cover thousands of outlets, but there is little evidence they deliver meaningful revenue to smaller publishers. The market is genuine where it exists. But it does not yet exist for most of the industry.”
But Langer also argued that AI firms may ultimately value types of journalism many publishers currently overlook.
“AI companies want what they cannot already get from the open web: underrepresented places, non-idealised contexts, court records, council minutes, regional language. That is a structural advantage for local and specialist newsrooms over the major brands — if they have done the work to make their archive licensable in the first place.”
Meanwhile James Grimmelmann, a law professor at Cornell Law School and Cornell Tech, is one of the leading academic experts on generative AI, copyright law, platform regulation and digital media economics, provides a far more sober outlook. He has been a prominent figure in internet-law and digital publishing debates for more than two decades and has often publicly criticised Silicon Valley’s approach to data and digital power.
Speaking to The European, his assessment was grim. He said: “There is not an individual market for licensing content to AI companies. The datasets they use are so large that any individual’s content could be removed without affecting the dataset’s utility. AI companies will simply remove the content rather than negotiate over the details. Only large media entities have the scale of content available to make negotiation and compensation worthwhile.”
But if scale is everything, what exactly do journalists and smaller news organisations still have that AI firms might actually want?
Right now small and regional publishers are reopening old databases formerly treated little more as digital storage, as they try to see if decades of reporting are now valuable AI assets. This means digging through vast digital collections packed with court reporting, council meeting minutes, local MP interviews, and years of tagged articles created long before the current AI boom began.
And it totally makes sense. Because in an age of ever-shrinking revenues and years of digital disruption, many are hoping AI licensing will offer a possible lifeline.
But how likely is it that their content is enough to tempt the titans of the AI industry to open their wallets?
Casey Newton is founder of influential tech newsletter Platformer, widely read by Silicon Valley’s top technology executives, policymakers and media insiders. Speaking to The European, he gave a stark warning that the economics still overwhelmingly favour companies with enormous quantities of material.
“My impression is that there is a market both for archival content and for real-time content. But archival content doesn’t pay as well. The reason is that Large Language Models (LLMs) are now so large that even a relatively large collection of archival material will still make up less than 1 percent of the training data of any model. I would be surprised if licensing my content to an LLM would increase my revenue by even 5 percent this year.”
He also warned that AI companies are aggressively seeking as much material as possible.
“AI labs are voracious and want every last bit of data and metadata they can get their hands on.”
And this daunting dynamic is just another thing to add to the massive list of worries smaller publishers are already facing. And to make matters worse, many fear AI may just repeat the pattern of the social-media era, when platforms built enormous businesses around journalism while much of the news industry struggled financially.
The Future Market
Others also suggest a sense of hope by looking to the future.
Mark Lemley, William H. Neukom Professor at Stanford Law School and director of the Stanford Program in Law, Science, and Technology, is a leading legal scholar on AI and intellectual property. Speaking to The European, he said the current licensing market for model training is still “largely limited to either high-profile news sources like the New York Times or to entities like Getty Images that can aggregate large amounts of content.”
But he believes newer AI systems based on retrieval-augmented generation — known could prove interesting for publishers.
“Companies using RAG may need to license content from all news sources. That could force AI firms into ongoing relationships with publishers rather than one-off scraping.”
Other small publishers say “specialised journalism” could even prove the way forward.
Isabelle Szczepanski is co-founder and editorial director of Paris-based media and technology publication ElectronLibre, which is run by just three journalists and a tech specialist. She believes publishers may ultimately find more opportunity in AI systems built around continuous access to specialised journalism rather than one-off training deals.
“At ElectronLibre, we have taken a different approach by developing our own AI system based on retrieval-augmented generation,” she told The European.
The system allows subscribers to ask questions and receive answers grounded in the publication’s archive of reporting. Szczepanski said licensing systems built around ongoing access to current journalism may ultimately prove more useful than traditional model-training agreements.
“Licensing models that provide continuous access — not only to archives but also to up-to-date content — seem both more practical and more valuable for end users,” she said. “Content that is niche, analytical, or based on original reporting likely has greater value than widely duplicated general news. Structured content significantly enhances this value.”
And others agree that the long-term winners in AI licensing may not necessarily be the largest publishers, but the most trusted and specialised.
Speaking to The European, German national Petra Rulsch, a Dubai-based media strategist focused on AI and technology communications, said: “In the long run, I suspect the decisive factor will not simply be scale, but specialisation, credibility and structure,” she said. “Journalism may ultimately become part of the trust infrastructure underpinning future AI ecosystems.”
The ‘Platform Era’ All Over Again?
But others warn that AI will simply recreate the same concentration of power that obliterated much of the news industry during the platform era, when Google, Facebook, YouTube and later TikTok became the dominant gateways to online news and advertising.
Radsch, director of the Center for Journalism and Liberty at the Open Markets Institute, is a journalist and long-time critic of platform concentration and threats to independent media. She also co-authored the hard-hitting report Same Gatekeepers, New Tollbooths: Mapping the AI Content Licensing Market which was released just last month, and warned that AI systems were “cannibalizing the content they depend on to function”.
“The quality of AI outputs depends on an ongoing supply of quality human content,” Radsch wrote in the report. “Destroy the economic foundation of that content, and you degrade the intelligence of AI itself.”
This dire warning resonates deeply with many journalists who watched in horror as the social-media revolution devastated advertising revenues across local and regional newsrooms. And this all while technology platforms accumulated extraordinary power and wealth!
A damning 2024 study by the CREATe Centre, for example, found that 93% of freelance journalists had never received income from platform licensing deals.
For many freelancers, the fear is not just that years of reporting may already have been absorbed into AI systems without any realistic prospect of compensation. It is that AI-generated summaries and answer engines could gradually reduce direct traffic to news websites in much the same way social-media platforms weakened publishers’ direct relationships with readers during the previous decade.
Visibility Or Exploitation?
Jeff Jarvis, professor at the Craig Newmark Graduate School of Journalism at the City University of New York, is one of the most influential thinkers in digital journalism and media transformation.
Speaking to The European, he warned some publishers risk making themselves invisible as AI systems increasingly shape how people discover information online. And he dismissed many of the current AI publishing agreements as political manoeuvres rather than genuine markets.
“These deals are for PR and policy — large AI companies paying large media companies to lay off litigation and lobbying for legislation.”
And he gave a brutal warning to publishers, that blocking AI systems entirely may create long-term risks of them becoming invisibile.
“If AI models are not made aware of a publisher or author, then it will not know to include that source in its answers,” he said.
For some journalists, however, the main issue goes beyond just economics – it is about morals.
Ulrich Hottelet is a German freelance journalist specialising in artificial intelligence, IT security and data protection. He has worked with organisations including Siemens, IBM and the German Federal Ministry for Economic Affairs. Speaking to The European, Hottelet said journalist’s work must be respected in this debate.
“Without our intellectual and creative work, the billions in revenues generated by OpenAI, DeepSeek, Anthropic and others would not be possible,” he said. “The fact that we were not asked before our content and data were massively fed into model training is, in my opinion, a violation of copyright law and unacceptable.”
Has The Online Ship Already Sailed?
Journalists and small publishers are already struggling against the sheer scale and speed with which AI firms have already absorbed online information.
Wendalyn Nichols is a publishing strategist and AI-content licensing specialist whose work has focused on structured content, digital publishing strategy and data licensing. She previously led online Cambridge Dictionary content operations at Cambridge University Press. Speaking to The European, Nichols argued that many publishers may already have misunderstood the nature of the market.
“For the LLM builders, I would argue that the licensing opportunity is already gone. AI firms mostly didn’t license content in the first place: they made assumptions about what constituted fair use, pretty much helping themselves to whatever they could extract from digital sources. I don’t think small archives have commercial value if an individual journalist is trying to sell their archive. Once an organization has trained its AI algorithm on your data, it doesn’t need your data any longer. So there is just no reason to renew a licence….the algorithm cannot unlearn what it now has learned.”
